1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
|
%#
%# fields is a package for analysis of spatial data written for
%# the R software environment.
%# Copyright (C) 2024 Colorado School of Mines
%# 1500 Illinois St., Golden, CO 80401
%# Contact: Douglas Nychka, douglasnychka@gmail.edu,
%#
%# This program is free software; you can redistribute it and/or modify
%# it under the terms of the GNU General Public License as published by
%# the Free Software Foundation; either version 2 of the License, or
%# (at your option) any later version.
%# This program is distributed in the hope that it will be useful,
%# but WITHOUT ANY WARRANTY; without even the implied warranty of
%# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
%# GNU General Public License for more details.
%#
%# You should have received a copy of the GNU General Public License
%# along with the R software environment if not, write to the Free Software
%# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
%# or see http://www.r-project.org/Licenses/GPL-2
%##END HEADER
%##END HEADER
\name{RMprecip}
\alias{RMprecip}
\alias{RMelevation}
\alias{PRISMelevation}
\title{
Monthly total precipitation (mm) for August 1997 in the Rocky Mountain
Region and some gridded 4km elevation data sets (m).
}
\description{
\code{RMprecip} is a useful spatial data set of moderate size consisting of 806
locations.
\code{PRISMelevation} and \code{RMelevation} are gridded elevations for the
continental US and Rocky Mountain region at 4km resolution.
Note that the gridded elevations from the PRISM data product are
different than the exact station elevations. (See example below.)
}
\format{
The data set \code{RMprecip} is a list containing the following components:
\describe{
\item{x}{
Longitude-latitude position of monitoring stations. Rows names are station id codes consistent
with the US Cooperative observer network.
The ranges for these coordinates are [-111, -99] for longitude and [35,45] for latitude.
}
\item{elev}{
Station elevation in meters.
}
\item{y}{
Monthly total precipitation in millimeters.
for August, 1997
}
}
The data sets
\code{PRISMelevation} and
\code{RMelevation} are lists
in the usual R grid format for images and contouring
They have the following components:
\describe{
\item{x}{
Longitude grid at approximately 4km resolution}
\item{y}{
Latitude grid at approximately 4km resolution}
\item{z}{
Average elevation for grid cell in meters
}
}
These elevations and the companion grid formed the basis for the
103-Year High-Resolution Precipitation Climate Data Set for the
Conterminous United States
( see \url{https://prism.oregonstate.edu/documents/PRISM_downloads_FTP.pdf}
and also archived at the National
Climate Data Center. This work is authored by Chris Daly
\url{https://prism.oregonstate.edu} and his PRISM group but had some
contribution from the Geophysical Statistics Project at NCAR
and is an interpolation of the observational data to a 4km grid that
takes into account topography such as elevation and aspect.
}
\details{
Contact Doug Nychka for the binary file \code{RData.USmonthlyMet.bin}
and information on its source.
\preformatted{
# explicit source code to create the RMprecip data
dir <- "" # include path to data file
load(paste(dir, "RData.USmonthlyMet.bin", sep="/")
#year.id<- 1963- 1895
year.id<- 103
#pptAUG63<- USppt[ year.id,8,]
loc<- cbind(USpinfo$lon, USpinfo$lat)
xr<- c(-111, -99)
yr<- c( 35, 45)
station.subset<- (loc[,1]>= xr[1]) & (loc[,1] <= xr[2]) & (loc[,2]>= yr[1]) & (loc[,2]<= yr[2])
ydata<- USppt[ year.id,8,station.subset]
ydata <- ydata*10 # cm -> mm conversion
xdata<- loc[station.subset,]
dimnames(xdata)<- list( USpinfo$station.id[station.subset], c( "lon", "lat"))
xdata<- data.frame( xdata)
good<- !is.na(ydata)
ydata<- ydata[good]
xdata<- xdata[good,]
test.for.zero.flag<- 1
test.for.zero( unlist(RMprecip$x), unlist(xdata), tag="locations")
test.for.zero( ydata, RMprecip$y, "values")
}
}
\examples{
# this data set was created the
# historical data taken from
# Observed monthly precipitation, min and max temperatures for the coterminous US
# 1895-1997
# NCAR_pinfill
# see the Geophysical Statistics Project datasets page for the supporting functions
# and details.
# plot
quilt.plot(RMprecip$x, RMprecip$y)
US( add=TRUE, col=2, lty=2)
# comparison of station elevations with PRISM gridded values
data(RMelevation)
interp.surface( RMelevation, RMprecip$x)-> test.elev
plot( RMprecip$elev, test.elev, xlab="Station elevation",
ylab="Interpolation from PRISM grid")
abline( 0,1,col="blue")
# some differences with high elevations probably due to complex
# topography!
#
# view of Rockies looking from theSoutheast
save.par<- par(no.readonly=TRUE)
par( mar=c(0,0,0,0))
# fancy use of persp with shading and lighting.
persp( RMelevation, theta=75, phi= 15,
box=FALSE, axes=FALSE, xlab="", ylab="",
border=NA,
shade=.95, lphi= 10, ltheta=80,
col= "wheat4",
scale=FALSE, expand=.00025)
# reset graphics parameters and a more conventional image plot.
par( save.par)
image.plot(RMelevation, col=topo.colors(256))
US( add=TRUE, col="grey", lwd=2)
title("PRISM elevations (m)")
}
\keyword{datasets}
% docclass is data
% Converted by Sd2Rd version 1.21.
|
